Simulating computer systems: techniques and tools
Simulating computer systems: techniques and tools
2-D Shape Classification Using Hidden Markov Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
The impact of mobility on cellular network configuration
Wireless Networks
The predictive user mobility profile framework for wireless multimedia networks
IEEE/ACM Transactions on Networking (TON)
The Mold Mobility Model for Mobile Wireless Networks
WICON '05 Proceedings of the First International Conference on Wireless Internet
Dynamic channel reservation based on mobility in wireless ATM networks
IEEE Communications Magazine
Computers and Electrical Engineering
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The multimedia services are getting to become the major trend in next-generation cellular networks. Call admission control (CAC) plays the key role for guaranteeing the quality of service (QoS) in cellular networks. The goal which keeps both the call dropping probability (CDP) and call blocking probability (CBP) below a certain level is more difficult owing to user indeterminate mobility. In this paper, the Hidden Markov Models (HMMs) concept which is suitable for solving a dynamic situation is introduced and applied to the call admission control policy. The prediction of user mobility can be modeled and resolved as the decoding problem of the HMMs. According to the prediction result, the proposed CAC method can reserve appropriate bandwidths for a handoff call beforehand. Thus, the call dropping probability can be kept below a lower level. Moreover, the call blocking probability is not sacrificed too much since the proposed method can reserve the suitable bandwidths in the appropriate cells but not reserve stationary ones which are always adopted by traditional CAC methods. Therefore, the proposed method not only can satisfy both CDP and CBP issues, but also improve the system utilization.